This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises.
This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
About the Author
Katarzyna Kopczewska is an associate professor at University of Warsaw, Faculty of Economic Sciences. As a quantitative economist, she deals with spatial modelling of geolocalised economic processes - location and co-location, agglomeration, concentration, diffusion, spatial interactions in relation to economic phenomena, companies and real estate but also regional policy or public-sector activities. She conducts methodological research on the implementation of data science methods for spatial analysis and combining them with classical spatial statistics and econometrics in R. She combines quantitative solutions with theory and problems of regional science and economic geography. She serves at the European Regional Science Association (ERSA).